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Jonathan Taylor
, Robert Tibshirani
, and Bradley Efron
- The ‘miss rate’ for the analysis of gene expression data
Biostat 6: 111-117.
Abstract 1 of 1
Biostatistics Vol. 6 No. 1 © Oxford University Press 2005; all rights reserved.
The ‘miss rate’ for the analysis of gene expression data
Department of Statistics, Stanford University, Stanford, CA 94305, USA jonathan.taylor{at}stanford.edu
Department of Health Research & Policy and Department of Statistics, Stanford University, Stanford, CA 94305, USA
Departments of Statistics, and Health Research & Policy, Stanford University, Stanford, CA 94305, USA
* To whom correspondence should be addressed.
Multiple testing issues are important in gene expression studies, where typically thousands of genes are compared over two or more experimental conditions. The false discovery rate has become a popular measure in this setting. Here we discuss a complementary measure, the ‘miss rate’, and show how to estimate it in practice.